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Managing Data as a Product

You're reading from   Managing Data as a Product Design and build data-product-centered socio-technical architectures

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Product type Paperback
Published in Nov 2024
Publisher Packt
ISBN-13 9781835468531
Length 368 pages
Edition 1st Edition
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Author (1):
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Andrea Gioia Andrea Gioia
Author Profile Icon Andrea Gioia
Andrea Gioia
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Toc

Table of Contents (18) Chapters Close

Preface 1. Part 1: Data Products and the Power of Modular Architectures
2. Chapter 1: From Data as a Byproduct to Data as a Product FREE CHAPTER 3. Chapter 2: Data Products 4. Chapter 3: Data Product-Centered Architectures 5. Part 2: Managing the Data Product Lifecycle
6. Chapter 4: Identifying Data Products and Prioritizing Developments 7. Chapter 5: Designing and Implementing Data Products 8. Chapter 6: Operating Data Products in Production 9. Chapter 7: Automating Data Product Lifecycle Management 10. Part 3: Designing a Successful Data Product Strategy
11. Chapter 8: Moving through the Adoption Journey 12. Chapter 9: Team Topologies and Data Ownership at Scale 13. Chapter 10: Distributed Data Modeling 14. Chapter 11: Building an AI-Ready Information Architecture 15. Chapter 12: Bringing It All Together 16. Index 17. Other Books You May Enjoy

Summary

In this chapter, we have seen how to identify a data product, starting from a business case. We first saw how to use domain-driven design to model a problem space, in order to find the problems of interest and then the best solutions. The problem space for an organization coincides with its business domain. To simplify its analysis, it is necessary to decompose it into smaller and easier-to-model parts. Starting from the business architecture, we used business capabilities and their instances at the operational structure level to determine the boundaries of the various parts of the problem space and the solution space, respectively.

We then used event storming to analyze the business processes of interest to the business strategy, in order to determine the business cases useful for its implementation. Again, using event storming, we saw how to identify data products from business cases.

Finally, we saw how to manage the overall portfolio of defined data products, in order...

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